Reduction of Gadolinium-Based Contrast Agents in MRI Using Convolutional Neural Networks and Different Input Protocols: Limited Interchangeability of Synthesized Sequences With Original Full-Dose Images Despite Excellent Quantitative Performance.
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| Title: | Reduction of Gadolinium-Based Contrast Agents in MRI Using Convolutional Neural Networks and Different Input Protocols: Limited Interchangeability of Synthesized Sequences With Original Full-Dose Images Despite Excellent Quantitative Performance. |
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| Authors: | Haase R, Pinetz T; Institute of Applied Mathematics, Rheinische Friedrich-Wilhelms-Universität Bonn, Bonn, Germany., Bendella Z; From the Department of Neuroradiology, University Medical Center Bonn, Rheinische Friedrich-Wilhelms-Universität Bonn., Kobler E; From the Department of Neuroradiology, University Medical Center Bonn, Rheinische Friedrich-Wilhelms-Universität Bonn., Paech D, Block W; From the Department of Neuroradiology, University Medical Center Bonn, Rheinische Friedrich-Wilhelms-Universität Bonn., Effland A; Institute of Applied Mathematics, Rheinische Friedrich-Wilhelms-Universität Bonn, Bonn, Germany., Radbruch A, Deike-Hofmann K |
| Source: | Investigative radiology [Invest Radiol] 2023 Jun 01; Vol. 58 (6), pp. 420-430. Date of Electronic Publication: 2023 Jan 28. |
| Publication Type: | Journal Article; Research Support, Non-U.S. Gov't |
| Journal Info: | Publisher: Lippincott Williams & Wilkins Country of Publication: United States NLM ID: 0045377 Publication Model: Print-Electronic Cited Medium: Internet ISSN: 1536-0210 (Electronic) Linking ISSN: 00209996 NLM ISO Abbreviation: Invest Radiol Subsets: MEDLINE |
| Database: | MEDLINE Ultimate |
| ISSN: | 1536-0210 |
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| DOI: | 10.1097/RLI.0000000000000955 |
